Introduction

Antibody–drug conjugates (ADC) represent an important class of therapeutic modalities for cancer (1). By conjugating a potent cytotoxic payload to targeted antibody, ADCs such as ADCETRIS® (brentuximab vedotin) and KADCYLA® (ado-trastuzumab emtansine) have offered novel treatment options for Hodgkin lymphoma and HER2+ breast cancer, respectively (2, 3). The key driver for the clinical activity of ADCs is attributed to the targeted delivery of a payload, which enters the cell through endocytic and lysosomal trafficking pathways. Once processed by lysosomal proteases (e.g., cathepsins), the released payload either induces apoptosis through disruption of microtubules (in the case of auristatins and maytansines), or nuclear DNA (in the case of pyrrolobenzodiazepine dimers and calicheamicin). In addition, after antigen-mediated drug release has occurred, some membrane permeable payloads (such as DM1, MMAE, and PBDs) have been shown to mediate bystander killing of adjacent tumor cells regardless of whether the targeted antigen is expressed (4, 5). Although these mechanisms of action have been demonstrated in vitro and in vivo, antigen-mediated drug release does not account for all the potent antitumor activities observed in the clinic (6). In fact, some diffuse large B-cell lymphoma (DLBC) patients with minimal or undetectable CD30 expression on their lymphoma cells responded to brentuximab vedotin in a phase II clinical trial (7, 8). Similarly, it has been reported that CD22 and CD79b expression is not required for patients to respond to ADCs targeting these receptors (6). These clinical observations raise the possibility that factors beyond target antigen expression on the cancer cells may be contributing to ADC antitumor activity (9, 10).

Engagement between cancer cells and the tumor microenvironment has been proposed as one of the hallmarks of cancer (11, 12). In particular, the infiltrating immune cells have been shown to be co-opted to promote tumor development and progression (13, 14). Numerous studies have shown that infiltration of tumor-associated macrophages (TAM) often correlates with poor prognosis in multiple types of malignancies. Not surprisingly, infiltrating immune cells can also influence the response to anticancer therapies (15, 16). Indeed, TAMs—a prominent subpopulation of the infiltrating immune cells—have been linked to the response to conventional chemotherapies and targeted anticancer agents (16). On the one hand, infiltrating TAMs may reduce sensitivity to paclitaxel and gemcitabine through suppression of CD8+ T cell activity (17, 18). On the other hand, TAMs can be crucial for executing the effector functions of certain antibodies. For example, trastuzumab has been shown to trigger macrophage engulfment of human epidermal growth factor receptor 2 (HER2)-positive cells (19, 20). These observations suggest the potential contribution of TAMs to the antitumor activity of antibody-based therapies.

Assessing ADC antitumor activity often relies on comparing tumor growth in xenograft models. While most such studies support the antigen-specific activities of targeted ADCs (21, 22), we occasionally have observed a significant growth delay in tumors treated with non-binding controls, including a humanized IgG conjugated to the protease-cleavable monomethyl auristatin E drug linker (hIgG-vcMMAE; ref. 23). For example, while treatment with αLIV1-vcMMAE ADC led MCF-7 tumors to complete tumor regression for 50 days, these tumors also responded to hIgG-vcMMAE treatment, undergoing an evident growth delay (Supplementary Fig. S1B; ref. 24). Understanding the unexpected activity of hIgG-vcMMAE in vivo may help to better characterize the mechanisms of ADC drugs in clinic.

Here, we evaluate the roles of tumor microenvironment on ADC antitumor activity in xenograft models, by comparing the antitumor activity and intratumoral drug concentrations resulting from targeted and non-targeted (hIgG-vcMMAE) monomethyl auristatin E (MMAE) conjugates. Our results suggest non-targeted ADCs can bind to F4/80+ TAMs, the abundance of which correlated with the antitumor activity of non-targeted ADCs in lymphoma and breast cancer models in vivo. Moreover, Fc gamma receptor (FcγR) binding-impaired hIgG1V1–vcMMAE conjugate was inactive in three xenograft models with high TAM infiltration, demonstrating that TAM-mediated ADC activity is likely due to Fc–FcγR interactions.

Materials and Methods

Xenograft studies and treatment

All animal studies were performed according to Institutional Animal Care and Use Committee guidelines. L-428(ACC197), KM-H2(ACC8), DOHH-2(ACC47), Karpas 299 (ACC31), and L-82(ACC597) cells were purchased from the German Collection of Microorganisms and Cell Cultures (DSMZ) between 2012 and 2013. Of note, Karpas 299 cells were originally provided by Dr. Karpas from the University of Cambridge (UK) in 1998. SU-DHL-8(CRL2961) was purchased from American Type Culture Collection (ATCC) in 2013. These cell lines were all authenticated by IDEXX Laboratories (MO). Five million L-428 and KM-H2 cells were subcutaneously injected to NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice (NSG, The Jackson Laboratory) to establish xenografts. DOHH-2, SU-DHL-8, and Karpas 299 cells were implanted in severe combined immune deficient mice (SCID). BR620 was a triple-negative breast cancer patient-derived xenograft model passaged in NSG mice (The Jackson Laboratory). Tumor-bearing animals were treated with ADCs intraperitoneally (i.p.) when the tumor volume is between 100 and 200 mm3. Tumors were measured with a digital caliper twice a week and the tumor volume is calculated using the formula ½ × length × width2. Intratumoral MMAE from tumors was prepared and measured using mass spectrometry as previously described (25).

IHC and flow cytometry

IHC on formalin fixed paraffin embedded xenograft tissues was performed using a Bond autostainer (Leica, Germany). Slides were deparaffinzied and antigen was retrieved in heated EDTA buffer. Macrophages were stained with rabbit anti-mouse F4/80 (Abcam), while ADCs were stained with anti-MMAE antibody (SG15.22, Seattle Genetics). Horseradish peroxidase-3,3′-diaminobenzidine (HRP-DAB) and alkaline phosphatase-fast red was used to detect bound primary antibodies. Hematoxylin was used to counter stain nuclei. Images were acquired on an Olympus BX41 microscope equipped with a Nikon DS-Fi1 camera.

Antibody–drug conjugates

Antibodies used for conjugation were all described previously (26). Anti-CD30 antibody was cAC10; Ab1-vcMMAE recognizes a surface receptor that is ubiquitously expressed and rapidly internalized (Seattle Genetics). Monomethyl auristatin E (MMAE) or monometheyl auristatin F (MMAF) was conjugated to antibodies with an average drug: antibody ratio of 4.

Statistical analysis

Tumor volume was plotted in Prism software (GraphPad). In general, two-way ANOVA analysis was used to compare the difference between each treatment agents, unless specified otherwise in the figures.

Results

Antigen-independent antitumor activity of ADCs in L-82 and MCF-7 xenografts

Consistent with most reports on xenograft response to targeted ADCs, tumors established from anaplastic large cell lymphoma L-82 expressed CD30 and went into complete regression after a single dose of αCD30-vcMMAE for 50 days. hIgG-vcMMAE treatment resulted in an initial complete remission for 10 days, followed by regrowth of tumor (Supplementary Fig. S1A). The moderate antitumor activity of hIgG-vcMMAE was also previously reported in MCF-7 xenograft model (Supplementary Fig. S1B; ref. 24). These observations illustrate while the targeting ADCs are certainly more active, the non-binding hIgG-vcMMAE can also have pronounced antitumor activities in vivo.

Intratumoral drug release by hIgG-vcMMAE

We have previously shown that intratumoral MMAE release correlated with ADC antitumor activity in vivo (5). To understand the antigen-independent activities of non-binding ADCs, we first determined whether tumors can process hIgG-vcMMAE and release MMAE. A panel of nine xenograft tumor models, including three Hodgkin lymphoma cell lines (L-428, KM-H2, and L540cy), two anaplastic large cell lymphoma cell lines (Karpas-299 and L-82), two acute myeloid leukemia cell lines (TF1α and THP-1), one Burkitt lymphoma (Ramos), and a renal cell carcinoma cell line (786-O), were treated with hIgG-vcMMAE at 3 mg/kg (once i.p.) and collected to measure intratumoral MMAE concentration 72 hours post dose. Liquid chromatography–mass spectrometry analysis revealed that MMAE was generated in these tumors, although at varying concentrations (range, 23–193 nmol/L; Supplementary Fig. S1C). This result suggests that tumors can process non-targeted hIgG-vcMMAE in vivo, although some may do so better than others. Depending on the intrinsic sensitivity of tumor cells, MMAE released from non-targeted hIgG-vcMMAE may accumulate in the tumor microenvironment to concentrations sufficient to mediate tumor cell death.

To better characterize the kinetics of hIgG-vcMMAE–induced activity, we measured the tumor growth after the treatment of a targeting ADC (αCD30-vcMMAE) or hIgG-vcMMAE in the L-428 tumors, in parallel to intratumoral MMAE concentration over a 10-day period. A single injection of 2 mg/kg αCD30 -vcMMAE or hIgG-vcMMAE induced stable disease in these tumors (Fig. 1A). Released MMAE concentration increased during the first three days and slowly decreased in the tumor. Importantly, hIgG-vcMMAE and αCD30-vcMMAE yielded comparable MMAE exposure in the tumor (669 vs. 907 day. nmol/L; Fig. 1B). These data suggest that, despite its non-binding nature, hIgG-vcMMAE was processed within the tumor microenvironment to release its payload without engaging any antigen on the tumor cells.

Antigen-independent antitumor activity correlates with intratumoral MMAE release in L-428 xenograft. A, Tumor growth of L-428 tumors, after the treatment of αCD30-vcMMAE or hIgG-vcMMAE (both ADCs given at 2 mg/kg, once i.p.), n = 8 per group. Using two-way ANOVA test p < 0.0001 (untreated vs. hIgG1-vsMMAE); p = 0.87 (hIgG1-vcMMAE vs. αCD30-vcMMAE). B, In a parallel cohort of animals, L-428 tumors were collected and intratumoral MMAE concentration was measured by LC/MS following ADC treatment, n = 3 per time point, p = 0.06 by a two-way ANOVA test. The efficacy study has been repeated at least twice at the 3-mg/kg dose level, while the LC/MS measurement was performed once as shown in B.

We next evaluated how the hIgG ADCs were processed in the L-428 tumors. First, we compared the activity of hIgG-vcMMAE and hIgG-vcMMAF, two ADCs which only differ in the released payload. Released MMAE is more membrane permeable than MMAF and can mediate bystander killing in vivo (5, 27). Anti-CD30 ADCs utilizing either MMAE or MMAF led to regression of CD30+ L-428 tumors, suggesting both payloads are potent in vivo (Fig. 2A). Interestingly, although both hIgG-vcMMAE and hIgG-vcMMAF released payloads in the tumors, only hIgG-vcMMAE caused a delay of tumor growth (Fig. 2A and B). These data are consistent with our recent observation that MMAE is significantly more membrane permeable relative to MMAF enabling it to mediate bystander tumor cell killing with the tumor microenvironment.

Membrane permeability of payload and antigen-independent antitumor activity. A, L-428 tumors were treated with targeting αCD30-vcMMAE and αCD30-vcMMAF ADCs, or non-binding hIgG-vcMMAE and hIgG-vcMMAF ADCs. All ADCs were given once i.p. at 3 mg/kg, n = 5 per group, p < 0.001 (hIgG-vcMMAE vs. hIgG-vcMMAF) by a two-way ANOVA test. B, Structure of MMAE and MAMF. LC/MS measurement of intratumoral released payload concentration in L-428 tumors collected three days after treatment of indicated ADCs. n = 3 for hIgG-vcMMAE and n = 2 for all other groups. Experiment shown in A has been repeated once more.

TAMs can process ADCs in L-428 tumors

We next performed IHC analysis for several components in the tumor microenvironment, including collagen, endothelial cells, and macrophages, to identify the mechanism underlying processing of non-targeted hIgG-vcMMAE. A distinguishing feature of L-428 tumors was the significant amount of macrophage infiltrates (Fig. 3A), as illustrated by the macrophage marker F4/80 staining. Costaining of F4/80 and anti-auristatin antibody revealed that F4/80-positive macrophages colocalized with hIgG-vcMMAE ADCs in the L-428 tumors, whereas most of the F4/80-negative cells, including L-428 tumor cells, were not stained by the anti-auristatin antibody (Fig. 3A). The physical interaction between hIgG-vcMMAE and TAMs was further confirmed by flow cytometric analysis showing that F4/80 expressing murine host macrophages retrieved from hIgG-vcMMAE-treated L-428 xenografts could be recognized by an anti-auristatin antibody (Fig. 3B). Therefore, hIgG-vcMMAE can bind to TAMs in vivo.

We then stained a panel of xenograft models to evaluate whether abundance of TAMs correlated with hIgG-vcMMAE mediated antitumor activity. Using F4/80 IHC, we found L-428, KM-H2, and BR620 (a patient-derived triple-negative breast cancer model) contain abundant TAMs (Fig. 4A). In line with our hypothesis, hIgG-vcMMAE treatment resulted in tumor remission or significant growth delay in these tumor models (Fig. 4B). For example, 3 mg/kg hIgG-vcMMAE caused remission and growth delay in L-428 tumors. Same treatment with hIgG-vcMMAE led to growth delay in the KM-H2 xenografts, although the growth delay was shorter than a CD30-targeting ADC. In the BR620 model, hIgG-vcMMAE also caused a significant growth delay.

In contrast, hIgG-vcMMAE was not active in xenograft models lacking TAMs. For example, TAMs were not found in tumors from DOHH-2 (B-cell non-Hodgkin lymphoma), SU-DHL-8 (large cell B lymphoma), and Karpas 299 (anaplastic large cell lymphoma; Fig. 4C). Concordantly, treatment of hIgG-vcMMAE had no impact the growth of DOHH-2 and SU-DHL-8 xenografts, and a minor delay of growth in Karpas-299 xenografts (Fig. 4D). Importantly, a positive control ADC (Ab1-vcMMAE) induced tumor growth delay in DOHH-2 and remission in SU-DHL-8 tumors, suggesting that (i) these models were sensitive to the payload MMAE and (ii) target-mediated ADC internalization and payload release mechanisms were intact in these models. Similarly, αCD30-vcMMAE induced complete remission of Karpas 299 tumors. Collectively, these data suggest the abundance of TAMs in preclinical tumor models may contribute to the antitumor activity of non-binding ADCs.

To further understand the mechanisms by which TAMs interact with ADCs, we generated a G1V1 mutant of the hIgG1 (E233P:L234V:L235A), which has profoundly reduced binding to CD64 (FcγR1) for both antibody and ADC (Supplementary Fig. S3; ref. 29). We then compared the activity of hIgG-vcMMAE and hIgG1V1-vcMMAE in the L-428 xenograft model. As shown previously, a single dose of 3 mg/kg hIgG-vcMMAE resulted in a 30-day regression of L-428 tumors. In contrast, hIgG1V1-vcMMAE did not mediate any apparent tumor regression and gave limited growth delay of L-428 tumors (Fig. 5A). In the Hodgkin lymphoma model KM-H2, while 3 mg/kg single dose of hIgG-vcMMAE yielded remission for a week and followed by growth delay for 10 more days, hIgG1V1-vcMMAE had no obvious impact on the growth of the tumors (Fig. 5B). In the patient-derived xenograft model BR620, 4 doses of 3 mg/kg hIgG-vcMMAE led to tumor regression and growth delay for 4 weeks. On the other hand, these tumors did not respond to hIgG1V1-vcMMAE at the same dose level (Fig. 5C). These three studies suggest that abrogating FcγR interaction reduces TAM-mediated ADC activity.

Fc receptor–ADC interaction is required for TAM-mediated ADC activity. A, Growth responses of L-428 tumors after the treatment of hIgG-vcMMAE and hIgG1V1-vcMMAE. Both ADCs were given at 3 mg/kg once ip, n = 5 per group. B, Growth kinetics of KM-H2 tumors after the treatment of hIgG-vcMMAE and hIgG1V1-vcMMAE (3 mg/kg once i.p.), n = 5 per group. C, Tumor growth of BR620 patient-derived xenograft models after the treatment of hIgG-vcMMAE and hIgG1V1-vcMMAE (3 mg/kg, q4dx4 i.p.), n = 5 per group. D, KM-H2 xenograft that were either untreated, received hIgG1-vcMMAE, or received hIVIg 24 hours prior to hIgG1-vcMMAE. hIVIg was given at 10 mg/kg iv; hIgG1-vcMMAE was given at 3 mg/kg once i.p., n = 5 per group. L-428 studies were repeated separately two more times. KM-H2 and BR-620 studies were performed once, respectively.

An alternative method to reduce the Fc–FcγR interaction is to saturate the plasma compartment with excess IgG. We treated KM-H2 tumor-bearing mice with 10 mg/kg human intravenous immunoglobulin (hIVIg) one day prior to the ADC administration. Mice receiving hIVIg had a shorter growth delay response to the hIgG-vcMMAE treatment (Fig. 5D). This result suggests the interaction between host FcγR and ADCs can be attenuated by introducing circulating IgG. Collectively, these data indicate that Fc binding function of the ADC was required for TAM-mediated antitumor activity.

Discussion

With the development of ADCETRIS® (brentuximab vedotin) and KADCYLA® (ado-trastuzumab emantasine), ADCs have become a major class of novel drugs developed for the treatment of cancer. More ADC drugs have demonstrated responses in indications that were challenging to treat, such as acute myeloid leukemia and glioblastoma (30, 31). However, the mechanisms by which ADCs exert antitumor effects independent of ADC-target interaction still remain unclear. For example, while CD30 is detected in ∼25% of DLBCL samples (32–34), brentuximab vedotin has surprisingly achieved a 44% objective response rate in patients with relapsed/refractory DLBCL with variable CD30 expression in a recent phase II trial (7). On the other hand, ADCs targeting pan-B cell markers (e.g., CD19, CD22, and CD79b) resulted in response rate between 31% and 54% (35, 36). Collectively, these clinical studies suggest other factors are involved in ADC activities in addition to antigen expression.

Antigen-independent antitumor activity in xenograft models

While mounting evidence has shown that ADCs mediate antigen-specific cytotoxicity in vitro, the antitumor activity of ADCs in vivo is only partially explained by antigen-specific uptake and processing. For example, in tumors displaying heterogeneous antigen expression, bystander killing of antigen-negative tumor cells can be mediated by membrane permeable payloads (4, 5). However, we and others reported that non-binding ADCs may lead to growth delay or remission in xenograft models (9, 24). In this study, we found hIgG-vcMMAE, a non-binding humanized IgG control, lead to tumor regression of two lymphoma and one breast cancer tumor models. Importantly, at the same dose level, hIgG-vcMMAE did not impact the growth of other lymphoma tumor models or many other carcinoma models (25, 37). The highly variable activity of hIgG-vcMMAE activity is consistent with the findings reported by others (10), indicating that ADCs may inhibit tumor growth in the absence of specifically targeted antigens, which may be associated with a clinical benefit for cancer patients. Interestingly, several studies have reported that a few patients with limited detectable target expression responded to ADC treatment (6, 7). While antigen expression can be heterogeneous with a given tumor and thus non-detectable on single biopsy of that tumor, more studies are required to better document such phenomena in future clinical trials and to elucidate the mechanisms underlying such observations.

TAMs and Fc interaction in therapeutic responses to ADCs

It is now widely accepted that the TAMs can influence disease progression and metastasis (11, 12). TAMs have been found to correlate with poor prognosis for cancers in breast, cervix, and bladder (13). In breast cancer, increased CD68+ macrophage counts correlated with shorter relapse-free survival and overall survival (38). In classical Hodgkin lymphoma, malignant Reed–Sternberg cells are outnumbered by nonmalignant stromal cells. Gene expression profiling and IHC analysis have suggested higher TAMs correlate with reduced rate of disease-specific survival in adult Hodgkin lymphoma (39, 40). The roles of TAMs in another type of lymphoma, DLBCL remain controversial (41). While TAMs have been linked to poor prognosis in patients who received chemotherapies such as CHOP, DLBCL patients with higher TAMs responded favorably when rituximab was given in combination with chemotherapy (42–45). All of these clinical studies demonstrate a critical role of TAMs in cancer.

In contrast to the growing consensus on the biology of TAMs, their involvement in the response to cancer therapeutics is more complex (46). Recently, TAMs were found to dampen the immune response and may drive resistance to chemotherapies such as gemcitabine, paclitaxel, and doxorubicin in animal models (17, 18). Monoclonal antibody-based therapies, such as rituximab and trastuzumab, may require the engagement of macrophages to assist phagocytosis. SGN-30, the parental antibody of brentuximab vedotin, was found to mediate ADCP in animal models (47). While these studies in general support the hypothesis that targeting antibodies can interact with macrophages, our study here is the first to demonstrate TAMs can interact with therapeutic ADCs even in the absence of antigen binding. The interaction between TAMs and ADCs was mediated through FcγRs, and such interaction led to ADC internalization and processing by the TAMs, with subsequent payload release within the tumor microenvironment. When the payload is membrane permeable, e.g., MMAE, the TAM-processed ADC can effectively mediate “bystander killing” of tumor cells. In addition, it is likely that other mechanisms contribute to processing of ADCs in the tumor microenvironment (10). Tumor-specific activation of Probody antibodies have been recently developed on the basis of extracellular metalloproteases (48). While it is beyond the scope of this study, further correlative studies in clinical trials on ADCs will be needed to more critically evaluate the role of TAMs and extracellular proteases in ADC processing, payload release, and antitumor effects in human patients.

TAMs may either promote or suppress tumor progression depending on how they are polarized, thus representing a potentially targetable cell population for cancer therapy (14). Indeed, an anti-CSF-1R antibody RG7155 led to depletion of TAMs and increases of CD8/CD4 T-cell ratio in various cancer models, and resulted in objective responses in patients with diffuse-type giant cell tumors (49). Our study clearly demonstrates the ability of TAMs to internalize ADCs using their FcγRs and subsequently process ADCs to release their payloads. Continued efforts to develop ADC drugs for targeted depletion of TAMs may provide another therapeutic avenue for treating cancer.

Disclosure of Potential Conflicts of Interest

L. Westendorf has ownership interest (including patents) in Seattle Genetics Stock. No potential conflicts of interest were disclosed by the other authors.

CD30 expression defines a novel subgroup of diffuse large B-cell lymphoma with favorable prognosis and distinct gene expression signature: a report from the International DLBCL Rituximab-CHOP Consortium Program Study.
Blood2013;121:2715–24.